Humans conventionally “teach” neural networks by providing a set of labeled data and asking the neural network to make decisions based on the samples it’s seen.

Applying the method to the binary classification of hair versus nonhair patches, we obtain a 2.2% performance increase using the heuristically trained NN over the current state-of-the-art hair segmentation method.